The Ducati Corse motorcycle team had a very successful season in the 2018 MotoGP, which ended when star rider Andrea Dovizioso was pipped to the world title by five-time champion Marc Márquez. While the racers and the engineers took home the plaudits, much of the credit should be shared with the IT team that supports them with data analysis.

Data helps determine the construction of the bikes, the performance of the riders and strategy of the team. To maximise the impact on the track, Ducati has partnered with NetApp to optimise the team’s data fabric and meet its unique and expanding data management needs.

Last year, Ducati introduced NetApp’s Hybrid Cloud Infrastructure (HCI) to more rapidly provide data to the team and drivers. NetApp claims its HCI delivers the power of an entire data centre to the race track, which enables faster data-driven decisions in a sport where miliseconds can make the difference between victory and defeat.

NetApp also helps Ducati manage around 200 applications and more than 300TB of data by providing real-time access to its All Flash FAS (AFF) storage system from anywhere in the world.

“It helps the team to reduce the time to check all is okay with the motorbikes, reduce the time to make a decision, and help the riders to be faster,” said Stefano Rendina, IT manager, Ducati Corse.

Data in MotoGPRacks holding all Ducati’s HPC infrastructure and other IT systems are carried on trucks to European events and by plane to other continents. Unlike Formula 1 cars, MotoGP bikes can’t be connected during practices, qualifying and races, so once the bike rides out of the garage it’s all down to the driver.

On the track, each Ducati motorbike is equipped with over 60 sensors that during each free practice session capture an average of more than 8GB of data on everything from tyre pressure to gear shift patterns while the riders describe their feelings at every point of the circuit.

The data isdownloaded at every garage stop through a cable connected to the setup software of the engine control unit.

If the analysis determines that changes are needed, a new setup can be deployed within minutes and uploaded in the bike to immediately boost the rider’s performance.

“It needs a lot of analysis engineers on the track during the race to do this but if you use an HCI with a dedicated virtual server you can reduce the time to check it’s also okay … and you can use different types of algorithms to decide which is the best solution,” says Rendina.

ImplementationNetApp Professional Services worked with the Ducati IT team to overhaul the manufacturer’s existing data management cloud infrastructure and replace it with a more powerful and modern IT framework, with integrated data protection and disaster recovery design.

In September 2018, they started testing how the new infrastructure would enable data analysis directly on the track, rather than having to send all the data to Ducati’s headquarters in Borgo Panigale, Italy.

They refined the system further with the testing team over a few events and then deployed the infrastructure directly on the official setup for a number of projects.

“The first one was to introduce the fresh array of Netapp on our HPC setup to make a calculation in a simulation with the aerodynamics department,” says Rendina.

“We developed over the last two or three years winglets on our motorbikes, a special aerodynamics part used to increase the power of motorbikes on the front row, help them stay on the tracks when you open the full throttle and you exit from a turn.

“This is one of the uses of NetApp on Ducati’s race department. The second one is we have started to introduce the HCI infrastructure as a convergence infrastructure directly on the tracks.”

The faster decision-making is already paying off and NetApp will continue to power Ducati’s data-driven team in the 2019 MotoGP, which starts on 10 March in Qatar.

Earl indicatorsThe early indications are that the race results could be even better. Ducati rider Dovizioso said the winter tests were the best he’d ever had in his six years at the time, but Rendina isn’t about to let his foot off the pedal.

“We want to understand how machine learning can help to check all data or a lot of data from 10 years ago to today to make a new strategy and to introduce something new to help develop the motorbikes of next year,” he says. “We never stop thinking about the next bike or about the next event.”